Project Title

Phonepe Pulse Data Visualization (Financial Domain)

Overview

This project aims to create an interactive data visualization tool for the Phonepe Pulse data available on GitHub. The tool provides user-friendly access to various metrics and statistics.

Features

   Data Extraction: Automates the process of fetching data from the Phonepe Pulse GitHub repository.
   
   Data Transformation: Cleans and processes the data using Python and Pandas.
   
   Database Integration: Stores the cleaned data in a MySQL database for efficient retrieval.
   
   Interactive Dashboard: Presents data using Streamlit and Plotly, offering dynamic visualizations.
   
   Data Retrieval: Connects to the PostgreSQL database to display data on the dashboard.
   
   Customization: Offers more interactive options for users to select different data visualizations.

Getting Started

Clone the GitHub repository.

Use Python, Pandas, and sql-connector-python for data processing.

Set up the MySQL database for data storage.

Create the interactive dashboard using Streamlit and Plotly.

Fetch data from the database for dashboard updates.

Technical Steps to Execute the Project

Step 1: Install Required Libraries

Before running the project, make sure to install the necessary libraries mentioned in the Dashboard.py file.

Step 2: Execute ETL Process

Use the ETL.py file to perform the Extract, Transform, Load (ETL) process on the Phonepe Pulse data.

Step 3: Run the Dashboard

Fork the Dashboard folder and run it in your local integrated development environment (IDE).

Step 4: Utilize the Phonepe_pulse Class

In this project, a Phonepe_pulse class has been created to manage the methods and processes.

Methods:

Dashboard: This method contains the code for the interactive dashboard, where data visualizations are presented.

    Note: Streamlit is used in this project to make our code visually appealing and to provide an eye-catching data presentation.

Skills Covered ✅ ⬇️

Python (Scripting)
ETL (Extract, Transform, Load)
MongoDB
SQL (Structured Query Language)
Data Management using PostgreSQL
User Interface: Streamlit
Data Visualization: Plotly-express
IDE: VSC

Results

This project delivers a user-friendly geo-visualization dashboard for exploring Phonepe Pulse data. Users can access and interact with various data visualizations through a web browser, gaining valuable insights from the Phonepe Pulse GitHub repository.

Connect Through LinkedIn For Queries !!!